tutorials/Data_import_and_visualization.ipynb

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    "# Data import and visualization in scCODA\n",
    "\n",
    "When performing compositional data analysis with scCODA, data can come from various sources.\n",
    "Also, it is often helpful to gain some insight on the data via exploratory plotting before running the scCODA model.\n",
    "In this tutorial notebook, we will\n",
    "\n",
    "- convert data from various sources for use with scCODA via `sccoda.util.cell_composition_data`\n",
    "- visualize the data with `sccoda.util.data_visualization`"
   ]
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   "source": [
    "# Imports\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import anndata as ad\n",
    "import warnings\n",
    "\n",
    "from sccoda.util import cell_composition_data as dat\n",
    "from sccoda.util import data_visualization as viz\n",
    "\n",
    "import sccoda.datasets as scd\n",
    "\n",
    "warnings.filterwarnings(\"ignore\")\n"
   ]
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    "## Data import\n",
    "\n",
    "scCODA uses the [anndata](https://github.com/theislab/anndata) format to handle cell count datasets and covariates in one object.\n",
    "Here, `adata.X` contains the cell counts as a numpy array with the dimensions $sample \\times celltype$, while `adata.obs` stores the covariate information for each sample as a pandas DataFrame.\n",
    "`adata.var` can contain additional information on the cell types.\n",
    "\n",
    "Besides manually creating the data object, `sccoda.util.cell_composition_data` gives methods to import data directly from a pandas DataFrame\n",
    "or from gene-based anndata objects like in [scanpy](https://github.com/theislab/scanpy).\n",
    "\n",
    "### Import from pandas\n",
    "\n",
    "To import data from a pandas DataFrame (with each row representing a sample), it is sufficient to specify the names of the metadata (covariate columns).\n",
    "As an example, we will use a dataset produced by [*Haber et al. [2017]*](https://www.nature.com/articles/nature24489),\n",
    "describing pathogen infection in the small intestinal epithelium of the mouse."
   ]
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     "text": [
      "            Mouse  Endocrine  Enterocyte  Enterocyte.Progenitor  Goblet  Stem  \\\n",
      "0       Control_1         36          59                    136      36   239   \n",
      "1       Control_2          5          46                     23      20    50   \n",
      "2       Control_3         45          98                    188     124   250   \n",
      "3       Control_4         26         221                    198      36   131   \n",
      "4  H.poly.Day10_1         42          71                    203     147   271   \n",
      "5  H.poly.Day10_2         40          57                    383     170   321   \n",
      "6   H.poly.Day3_1         52          75                    347      66   323   \n",
      "7   H.poly.Day3_2         65         126                    115      33    65   \n",
      "8          Salm_1         37         332                    113      59    90   \n",
      "9          Salm_2         32         373                    116      67   117   \n",
      "\n",
      "    TA  TA.Early  Tuft  \n",
      "0  125       191    18  \n",
      "1   11        40     5  \n",
      "2  155       365    33  \n",
      "3  130       196     4  \n",
      "4  109       180   146  \n",
      "5  244       256    71  \n",
      "6  263       313    51  \n",
      "7   39       129    59  \n",
      "8   47       132    10  \n",
      "9   65       168    12  \n"
     ]
    }
   ],
   "source": [
    "# Read data into pandas from csv\n",
    "\n",
    "cell_counts = scd.haber()\n",
    "\n",
    "print(cell_counts)"
   ]
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     "text": [
      "[[ 36.  59. 136.  36. 239. 125. 191.  18.]\n",
      " [  5.  46.  23.  20.  50.  11.  40.   5.]\n",
      " [ 45.  98. 188. 124. 250. 155. 365.  33.]\n",
      " [ 26. 221. 198.  36. 131. 130. 196.   4.]\n",
      " [ 42.  71. 203. 147. 271. 109. 180. 146.]\n",
      " [ 40.  57. 383. 170. 321. 244. 256.  71.]\n",
      " [ 52.  75. 347.  66. 323. 263. 313.  51.]\n",
      " [ 65. 126. 115.  33.  65.  39. 129.  59.]\n",
      " [ 37. 332. 113.  59.  90.  47. 132.  10.]\n",
      " [ 32. 373. 116.  67. 117.  65. 168.  12.]]\n",
      "            Mouse     Condition\n",
      "0       Control_1       Control\n",
      "1       Control_2       Control\n",
      "2       Control_3       Control\n",
      "3       Control_4       Control\n",
      "4  H.poly.Day10_1  H.poly.Day10\n",
      "5  H.poly.Day10_2  H.poly.Day10\n",
      "6   H.poly.Day3_1   H.poly.Day3\n",
      "7   H.poly.Day3_2   H.poly.Day3\n",
      "8          Salm_1          Salm\n",
      "9          Salm_2          Salm\n"
     ]
    }
   ],
   "source": [
    "data_mouse = dat.from_pandas(cell_counts, covariate_columns=[\"Mouse\"])\n",
    "\n",
    "# Extract condition from mouse name and add it as an extra column to the covariates\n",
    "data_mouse.obs[\"Condition\"] = data_mouse.obs[\"Mouse\"].str.replace(r\"_[0-9]\", \"\", regex=True)\n",
    "print(data_mouse.X)\n",
    "print(data_mouse.obs)"
   ]
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    "### Import from scanpy\n",
    "\n",
    "Cell type assignments are usually gained by clustering methods such as Louvain clustering.\n",
    "The [scanpy](https://github.com/theislab/scanpy) platform provides a way of performing a variety of such assignment methods.\n",
    "Even though scanpy also uses the anndata format, it does so on a level of $cell \\times gene$.\n",
    "To allow for quick transformation into scCODA's data format, some converter functions are available.\n",
    "\n",
    "We will explore them on the [Preprocessing and clustering 3k PBMCs tutorial dataset of scanpy](https://scanpy-tutorials.readthedocs.io/en/latest/pbmc3k.html).\n",
    "Since scCODA requires a distinction into samples, we will copy the dataset three times and add a new column `sample` to `adata.obs`.\n",
    "Also, we need some covariate metadata, which we also simulate for this tutorial."
   ]
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     "text": [
      "AnnData object with n_obs × n_vars = 700 × 765\n",
      "    obs: 'bulk_labels', 'n_genes', 'percent_mito', 'n_counts', 'S_score', 'G2M_score', 'phase', 'louvain'\n",
      "    var: 'n_counts', 'means', 'dispersions', 'dispersions_norm', 'highly_variable'\n",
      "    uns: 'bulk_labels_colors', 'louvain', 'louvain_colors', 'neighbors', 'pca', 'rank_genes_groups'\n",
      "    obsm: 'X_pca', 'X_umap'\n",
      "    varm: 'PCs'\n",
      "    obsp: 'distances', 'connectivities'\n"
     ]
    }
   ],
   "source": [
    "# read data\n",
    "adata = ad.read_h5ad(\"../data/10x_pbmc68k_reduced.h5ad\")\n",
    "print(adata)\n"
   ]
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    {
     "name": "stderr",
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     "text": [
      "Observation names are not unique. To make them unique, call `.obs_names_make_unique`.\n",
      "Observation names are not unique. To make them unique, call `.obs_names_make_unique`.\n"
     ]
    },
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     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AnnData object with n_obs × n_vars = 2100 × 765\n",
      "    obs: 'bulk_labels', 'n_genes', 'percent_mito', 'n_counts', 'S_score', 'G2M_score', 'phase', 'louvain', 'sample'\n",
      "    obsm: 'X_pca', 'X_umap'\n"
     ]
    }
   ],
   "source": [
    "# make three copys\n",
    "adata_1 = adata.copy()\n",
    "adata_1.obs[\"sample\"] = 1\n",
    "\n",
    "adata_2 = adata.copy()\n",
    "adata_2.obs[\"sample\"] = 2\n",
    "\n",
    "adata_3 = adata.copy()\n",
    "adata_3.obs[\"sample\"] = 3\n",
    "\n",
    "# join them together again\n",
    "adata_all = ad.concat([adata_1, adata_2, adata_3])\n",
    "print(adata_all)"
   ]
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     "text": [
      "  Cond\n",
      "1    A\n",
      "2    B\n",
      "3    A\n"
     ]
    }
   ],
   "source": [
    "# make covariate DataFrame\n",
    "\n",
    "cov_df = pd.DataFrame({\"Cond\": [\"A\", \"B\", \"A\"]}, index=[1,2,3])\n",
    "print(cov_df)"
   ]
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   "source": [
    "If we have one anndata object that contains the gene expression data for all samples, we can use `dat.from_scanpy`.\n",
    "We just need to specify the columns in `adata.obs` that contain the sample information and the clustering results, as well as the covariate data frame."
   ]
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     "text": [
      "AnnData object with n_obs × n_vars = 3 × 11\n",
      "    obs: 'Cond'\n",
      "    var: 'n_cells'\n"
     ]
    }
   ],
   "source": [
    "data_scanpy_1 = dat.from_scanpy(\n",
    "    adata_all,\n",
    "    cell_type_identifier=\"louvain\",\n",
    "    sample_identifier=\"sample\",\n",
    "    covariate_df=cov_df\n",
    ")\n",
    "print(data_scanpy_1)"
   ]
  },
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   "source": [
    "If there is one anndata object per sample, we can use `dat.from_scanpy_list` in the same way.\n",
    "Obviously, we do not need to specify a sample column now."
   ]
  },
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   "execution_count": 8,
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     "text": [
      "AnnData object with n_obs × n_vars = 3 × 11\n",
      "    obs: 'Cond'\n",
      "    var: 'n_cells'\n"
     ]
    }
   ],
   "source": [
    "data_scanpy_2 = dat.from_scanpy_list(\n",
    "    [adata_1, adata_2, adata_3],\n",
    "    cell_type_identifier=\"louvain\",\n",
    "    covariate_df=cov_df\n",
    ")\n",
    "print(data_scanpy_2)"
   ]
  },
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   "source": [
    "## Compositional data visualization\n",
    "\n",
    "Analyzing compositional data is not straightforward. scCODA provides some ways of visualizing the properties of a compositional dataset before analysis.\n",
    "We will showcase these functions on the data on pathogen infection of mice from [*Haber et al. [2017]*](https://www.nature.com/articles/nature24489).\n",
    "\n",
    "### Stacked barplot\n",
    "\n",
    "The most common representation of cell count data in genomic research are stacked barplots.\n",
    "In scCODA, these can be produced easily via `viz.stacked_barplot`.\n",
    "The function can either plot one stacked bar for each level of a covariate, or one stacked bar for each sample."
   ]
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\n",
      "text/plain": [
       "<Figure size 600x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 600x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Stacked barplot for each sample\n",
    "viz.stacked_barplot(data_mouse, feature_name=\"samples\")\n",
    "plt.show()\n",
    "\n",
    "# Stacked barplot for the levels of \"Condition\"\n",
    "viz.stacked_barplot(data_mouse, feature_name=\"Condition\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "### Grouped boxplots\n",
    "\n",
    "While stached barplots are a nice and compact way of representing compositional data, they omit crucial information about the data variance.\n",
    "Also, comparing the abundance of cell types that are not on the top or bottom of the bars can be hard.\n",
    "\n",
    "To combat this, scCODA also provides a visualization via boxplots crouped by cell type and condition via `viz.boxplots`.\n",
    "The function provides a lot of customization options, like log-scale plotting, representation as a faceted plot, or the addition of dots for each sample."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 600x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 8 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Grouped boxplots. No facets, relative abundance, no dots.\n",
    "viz.boxplots(\n",
    "    data_mouse,\n",
    "    feature_name=\"Condition\",\n",
    "    plot_facets=False,\n",
    "    y_scale=\"relative\",\n",
    "    add_dots=False,\n",
    ")\n",
    "plt.show()\n",
    "\n",
    "# Grouped boxplots. Facets, log scale, added dots and custom color palette.\n",
    "viz.boxplots(\n",
    "    data_mouse,\n",
    "    feature_name=\"Condition\",\n",
    "    plot_facets=True,\n",
    "    y_scale=\"log\",\n",
    "    add_dots=True,\n",
    "    cmap=\"Reds\",\n",
    ")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "### Finding a reference cell type\n",
    "The scCODA model requires a cell type to be set as the reference category. However, choosing this cell type is often difficult.\n",
    "A good first choice is a referenece cell type that closely preserves the changes in relative abundance during the compositional analysis.\n",
    "\n",
    "For this, it is important that the reference cell type is not rare, to avoid large relative changes being caused by small absolute changes.\n",
    "Also, the relative abundance of the reference should vary as little as possible across all samples.\n",
    "\n",
    "The visualization `viz.rel_abundance_dispersion_plot` shows the presence (share of non-zero samples) over all samples for each cell type\n",
    "versus its dispersion in relative abundance. Cell types that have a higher presence than a certain threshold (default 0.9) are suitable candidates for the reference and thus colored."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 600x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "viz.rel_abundance_dispersion_plot(\n",
    "    data=data_mouse,\n",
    "    abundant_threshold=0.9\n",
    ")\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.7",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}